Areas of Interest
- Computer Vision
- Machine Learning
- Natural Language Generation
- Human Computer Interaction
- Ph.D. in Electrical and Computer Engineering, Cornell University, Ithaca, NY, 2014
- B.Eng. in Electrical and Computer Engineering, The Cooper Union, New York, NY, 2009
Amir Sadovnik is an assistant professor in the EECS department at the University of Tennessee. He received his PhD from the School of Electrical and Computer Engineering at Cornell University and was advised by Prof. Tsuhan Chen as member of the Advanced Multimedia Processing Lab. Prior to arriving at Cornell he received his Bachelors in Electrical and Computer Engineering from The Cooper Union.
Prior to arriving at UT, Amir was an assistant professor at Lafayette College in Easton, PA. He spent four years mostly teaching undergraduate level courses in addition to working on undergraduate research. During his time at Lafayette he taught a variety of both introductory and advanced computer science courses. In addition, he helped redesign the introductory computer science course to make it more inclusive and was an active advocate for women in the field.
His research in the field of computer vision has been mostly driven by the way humans understand and interact with images. This human centered view has led him to work on new and exciting projects, which utilize tools from different fields (such as computer vision, signal processing, natural language processing, machine learning, etc.) and apply them in new ways.
His current research is mostly centered on using deep neural networks for tasks which tend to be more subjective such as evoked emotions, face similarity, and fashion compatibility. The subjective nature of these problems presents many interesting obstacles and opportunities which he explores in his research.